latinsquare {languageR}R Documentation

Simulated Latin Square data set with subjects and items

Description

Simulated lexical decision latencies with SOA as treatment, using a Latin Square design with subjects and items, as available in Raaijmakers et al. (1999).

Usage

data(latinsquare)

Format

A data frame with 144 observations on the following 6 variables.

Group
a factor with levels G1, G2 and G3, for groups of subjects
Subject
a factor with subjects labelled S1, ... S12.
Word
a factor with words labelled W1 ... W12.
RT
a numeric vector for reaction times.
SOA
a factor with levels long, medium, and short.
List
a factor with levels L1, L2, and L3 for lists of words.

Source

Raaijmakers, J.G.W., Schrijnemakers, J.M.C. & Gremmen, F. (1999) How to deal with "The language as fixed effect fallacy": common misconceptions and alternative solutions, Journal of Memory and Language, 41, 416-426.

Examples

## Not run: 
data(latinsquare)
library(lme4)
latinsquare.with = 
   simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = TRUE) 
latinsquare.without = 
   simulate.latinsquare.fnc(latinsquare, nruns = 1000, with = FALSE)
latinsquare.with$alpha05
latinsquare.without$alpha05
## End(Not run)

[Package languageR version 0.953 Index]